基于多级维纳滤波的盲信噪比估计  

Blind SNR Estimation Based on Multistage Wiener Filter

作　　者：谭晓波[1] 张杭[1] 

机构地区：[1]解放军理工大学通信工程学院,江苏南京210007

出　　处：《信号处理》2010年第11期1725-1729,共5页Journal of Signal Processing

摘　　要：提出了一种基于多级维纳滤波(MSWF:Multistage Wiener Filter)的盲信噪比估计算法。结合信号子空间分解理论,该方法利用基于相关相减算法(CSA:Correlation Subtraction Algorithm)的前向递推的多级维纳滤波器实现含噪信号空间分解,避免了传统方法对信号自相关矩阵进行复杂的特征值分解运算,并以此估计信号功率和噪声功率来完成盲信噪比估计。在加性高斯白噪声(AWGN)信道条件下进行信噪比估计仿真,仿真表明,当实际信噪比在-7～25dB范围内时,算法的估计标准偏差小于0.5dB,且性能优于常规方法。设定实际信噪比为10dB,当接收码元数目为100时,对所有仿真的调制方式的信噪比估计标准偏差小于0.35dB,证明了估计算法在小样本支撑环境下实现信噪比快速盲估计的能力。In this paper,an algorithm based on multistage wiener filter（MSWF：Multistage Wiener Filter） is proposed for blind SNR estimation.Combined with the signal subspace decomposition theory,the noise contained subspace decomposition can be achieved by CSA-MSWF（CSA：Correlation Subtraction Algorithm） forward iterations,this avoid the complex decomposition of the signal autocorrelation matrix in classical methods,so the power of the signal and noise could be obtained in this way,also the SNR estimation values. Simulation in Additive Gaussian noise channel（AWGN） proved that the performance of this approach is slightly better than traditional methods,and while the true SNR is -7～25dB,the standard deviation of SNR estimation is less than 0.5dB.When the codes received are 100 and the actual SNR is 10dB,the biases of SNR estimation are smaller than 0.35dB for all modulation types simulated here,it shows that the rapid ability of blind SNR estimation in the small samples supported environment of the estimator.

关 键 词：信噪比估计 子空间分解 多级维纳滤波器 匹配滤波 

分 类 号：TN911.7[电子电信—通信与信息系统]